CSCI 343 Quiz 5 Flashcards

1
Q

demographic data

A

consumers’ demographic info in social media (age, gender, education, geography, etc.)

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2
Q

product data

A

product data in social media, which are generated when a particular brand or product name is mentioned

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3
Q

psychographic data

A

the type of social media data that indicates consumers’ personality, interest, and lifestyle

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4
Q

behavioral data

A

past behavioral information in social media that supports to predict future action

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5
Q

referrals data

A

ratings, reviews, and non-verbal attitudes generate referral data

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6
Q

location data

A

real time location data of consumer

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7
Q

intention data

A

data in social media that indicates consumers’ future buying intentions and activity

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8
Q

topic modeling definition

A

detecting dominant themes or topics by sifting through a large body of captured text

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9
Q

purpose of topic modeling

A

helps to identify underlying themes/topics

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10
Q

opinion mining definition

A

focuses on the views, beliefs, and judgement rather than considering positive or negative sentiment

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11
Q

purpose of opinion mining

A

measures the views and beliefs based on the criteria that depend on the purpose of analysis

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12
Q

sentiment analysis definition

A

interpretation of data of public/consumer/user sentiments, evaluations, appraisals, attitudes, and emotions towards entities such as products, services, organizations, individuals, issues, events, topics, and their attributes

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13
Q

purpose of sentiment analysis

A

measures the individual, group, community’s emotions toward any types of events, products, services, brands, etc.

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14
Q

social network analysis definition

A

analysis of the social network made up of individuals called nodes and connected with other nodes with similar interest; data analysis technique includes number of nodes, frequency of edges

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15
Q

social network analysis is the only type of social media analysis that

A

looks more outward

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16
Q

purpose of social network analysis

A

measures the types and depth of relationship between the networks; predict a person’s beliefs based on their network

17
Q

trend analysis definition

A

predicting market trends or customer behavior using historical data

18
Q

purpose of trend analysis

A

forecasting sales, market share, customer growth, or movements in the stock market

19
Q

popularity prediction definition

A

collecting positive and negative opinion/ranks/feedbacks, shares and likes on certain subjects or events and to understand the level of current popularity and forecast the future based on the current evidence

20
Q

purpose of popularity prediction

A

allows organizations to forecast the future demand of products, services, or events

21
Q

customer engagement analysis definition

A

the process to prolong the conversation or events or activities with social media participants or users; without proper incentives it is difficult to create engagement for a long time

22
Q

purpose of customer engagement analysis

A

measure the success of the online activities; helps organization to understand the current situation and next action needed to be successful online

23
Q

visual analytics definition

A

iterative process that involves information gathering, processing, and decision making

24
Q

purpose of visual analytics

A

use graphical interfaces to present, explore, and confirm relationships among variables

25
Q

use bar charts to

A

compare data across categories

26
Q

use line charts to

A

view trends in data, usually over time (show a value evolving)

27
Q

instead of making a pie chart the focus of your dashboard, try using them to

A

drill down on other visualizations (add information)

28
Q

use maps to

A

show how location correlates with trends in your data

29
Q

use scatter plots to

A

investigate the relationship between different variables

30
Q

scatter plots are an effective way to give you a sense of

A

trends, concentrations, and outliers

31
Q

use Gantt charts to

A

display a project schedule or show changes in use or activity over time

32
Q

use bubble charts to

A

show the relationship between three or more measures

33
Q

use histograms to

A

understand the distribution of your data (how data falls into categories)

34
Q

use a bullet hart to

A

quickly compare a metric to a goal (“how are we doing”)

35
Q

use heat maps to

A

compare categorical data using color (best for presenting data sets with lots of categories)

36
Q

use highlight tables to

A

draw attention to detailed information

37
Q

use treemaps to

A

show data with multiple levels of categorization

38
Q

use box-and-whisker plots to

A

show the distribution of a data set; see how data is skewed towards one end and identify outliers

39
Q

use a candlestick chart for

A

showing financial data